Examining the impact of cognitive load on structure learning
6 agents, 12 issues
Method changes:
0
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0.25
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0.5
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0.75
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1
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Overall
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|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| high (N=51) |
low (N=37) |
high (N=46) |
low (N=54) |
high (N=41) |
low (N=56) |
high (N=53) |
low (N=43) |
high (N=45) |
low (N=38) |
high (N=236) |
low (N=228) |
|
| age | ||||||||||||
| Mean (SD) | 36.7 (12.4) | 34.4 (11.7) | 36.7 (12.1) | 37.4 (10.4) | 38.2 (13.2) | 35.3 (10.5) | 35.3 (10.6) | 35.9 (10.8) | 39.3 (11.8) | 38.9 (15.0) | 37.1 (12.0) | 36.4 (11.6) |
| Median [Min, Max] | 34.0 [20.0, 72.0] | 32.0 [21.0, 66.0] | 34.0 [19.0, 65.0] | 35.0 [19.0, 64.0] | 37.0 [18.0, 69.0] | 36.0 [20.0, 63.0] | 35.0 [18.0, 55.0] | 35.0 [20.0, 61.0] | 38.0 [22.0, 73.0] | 33.5 [19.0, 68.0] | 35.0 [18.0, 73.0] | 34.0 [19.0, 68.0] |
| race | ||||||||||||
| Asian | 4 (7.8%) | 4 (10.8%) | 6 (13.0%) | 4 (7.4%) | 6 (14.6%) | 12 (21.4%) | 4 (7.5%) | 5 (11.6%) | 3 (6.7%) | 5 (13.2%) | 23 (9.7%) | 30 (13.2%) |
| Black or African-American | 10 (19.6%) | 5 (13.5%) | 8 (17.4%) | 4 (7.4%) | 7 (17.1%) | 3 (5.4%) | 11 (20.8%) | 6 (14.0%) | 3 (6.7%) | 4 (10.5%) | 39 (16.5%) | 22 (9.6%) |
| Hispanic/Latinx | 6 (11.8%) | 2 (5.4%) | 0 (0%) | 6 (11.1%) | 2 (4.9%) | 5 (8.9%) | 4 (7.5%) | 5 (11.6%) | 3 (6.7%) | 1 (2.6%) | 15 (6.4%) | 19 (8.3%) |
| White | 31 (60.8%) | 26 (70.3%) | 31 (67.4%) | 37 (68.5%) | 24 (58.5%) | 36 (64.3%) | 33 (62.3%) | 26 (60.5%) | 35 (77.8%) | 26 (68.4%) | 154 (65.3%) | 151 (66.2%) |
| American Indian or Alaska Native | 0 (0%) | 0 (0%) | 1 (2.2%) | 2 (3.7%) | 1 (2.4%) | 0 (0%) | 1 (1.9%) | 1 (2.3%) | 1 (2.2%) | 1 (2.6%) | 4 (1.7%) | 4 (1.8%) |
| Other | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.4%) |
| Native Hawaiian or Other Pacific Islander | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.4%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.6%) | 1 (0.4%) | 1 (0.4%) |
| gender | ||||||||||||
| Another gender not listed here | 1 (2.0%) | 0 (0%) | 0 (0%) | 1 (1.9%) | 0 (0%) | 0 (0%) | 1 (1.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.8%) | 1 (0.4%) |
| Man | 25 (49.0%) | 15 (40.5%) | 25 (54.3%) | 25 (46.3%) | 14 (34.1%) | 23 (41.1%) | 28 (52.8%) | 17 (39.5%) | 22 (48.9%) | 19 (50.0%) | 114 (48.3%) | 99 (43.4%) |
| Non-binary | 1 (2.0%) | 2 (5.4%) | 1 (2.2%) | 0 (0%) | 0 (0%) | 1 (1.8%) | 1 (1.9%) | 1 (2.3%) | 1 (2.2%) | 0 (0%) | 4 (1.7%) | 4 (1.8%) |
| Woman | 24 (47.1%) | 20 (54.1%) | 20 (43.5%) | 28 (51.9%) | 27 (65.9%) | 32 (57.1%) | 23 (43.4%) | 25 (58.1%) | 20 (44.4%) | 18 (47.4%) | 114 (48.3%) | 123 (53.9%) |
| Prefer not to answer | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (4.4%) | 1 (2.6%) | 2 (0.8%) | 1 (0.4%) |
| matrix_acc | ||||||||||||
| Mean (SD) | 0.846 (0.183) | 0.936 (0.0865) | 0.837 (0.173) | 0.965 (0.0615) | 0.777 (0.244) | 0.931 (0.145) | 0.764 (0.248) | 0.892 (0.169) | 0.736 (0.243) | 0.924 (0.107) | 0.793 (0.223) | 0.931 (0.122) |
| Median [Min, Max] | 0.875 [0.250, 1.00] | 1.00 [0.750, 1.00] | 0.875 [0.250, 1.00] | 1.00 [0.750, 1.00] | 0.875 [0, 1.00] | 1.00 [0.125, 1.00] | 0.875 [0, 1.00] | 0.875 [0, 1.00] | 0.750 [0, 1.00] | 1.00 [0.625, 1.00] | 0.875 [0, 1.00] | 1.00 [0, 1.00] |
| as.factor(matrix_n_correct) | ||||||||||||
| 0 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (4.9%) | 0 (0%) | 2 (3.8%) | 1 (2.3%) | 1 (2.2%) | 0 (0%) | 5 (2.1%) | 1 (0.4%) |
| 1 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.4%) |
| 2 | 2 (3.9%) | 0 (0%) | 1 (2.2%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (3.8%) | 0 (0%) | 2 (4.4%) | 0 (0%) | 7 (3.0%) | 0 (0%) |
| 3 | 0 (0%) | 0 (0%) | 1 (2.2%) | 0 (0%) | 2 (4.9%) | 0 (0%) | 3 (5.7%) | 0 (0%) | 3 (6.7%) | 0 (0%) | 9 (3.8%) | 0 (0%) |
| 4 | 2 (3.9%) | 0 (0%) | 1 (2.2%) | 0 (0%) | 3 (7.3%) | 0 (0%) | 1 (1.9%) | 0 (0%) | 2 (4.4%) | 0 (0%) | 9 (3.8%) | 0 (0%) |
| 5 | 4 (7.8%) | 0 (0%) | 4 (8.7%) | 0 (0%) | 1 (2.4%) | 1 (1.8%) | 4 (7.5%) | 1 (2.3%) | 9 (20.0%) | 2 (5.3%) | 22 (9.3%) | 4 (1.8%) |
| 6 | 7 (13.7%) | 4 (10.8%) | 9 (19.6%) | 1 (1.9%) | 8 (19.5%) | 6 (10.7%) | 13 (24.5%) | 5 (11.6%) | 9 (20.0%) | 3 (7.9%) | 46 (19.5%) | 19 (8.3%) |
| 7 | 17 (33.3%) | 11 (29.7%) | 15 (32.6%) | 13 (24.1%) | 16 (39.0%) | 9 (16.1%) | 15 (28.3%) | 16 (37.2%) | 7 (15.6%) | 11 (28.9%) | 70 (29.7%) | 60 (26.3%) |
| 8 | 19 (37.3%) | 22 (59.5%) | 15 (32.6%) | 40 (74.1%) | 9 (22.0%) | 39 (69.6%) | 13 (24.5%) | 20 (46.5%) | 12 (26.7%) | 22 (57.9%) | 68 (28.8%) | 143 (62.7%) |
0
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0.25
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0.5
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0.75
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1
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Overall
|
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| high (N=2) |
low (N=4) |
high (N=3) |
low (N=2) |
high (N=3) |
low (N=3) |
high (N=5) |
low (N=1) |
high (N=4) |
low (N=7) |
high (N=17) |
low (N=17) |
|
| age | ||||||||||||
| Mean (SD) | 37.5 (7.78) | 33.8 (3.10) | 44.0 (13.5) | 31.0 (5.66) | 30.7 (2.31) | 41.3 (19.1) | 39.4 (8.59) | 27.0 (NA) | 25.5 (5.45) | 38.1 (12.3) | 35.2 (9.97) | 36.2 (11.1) |
| Median [Min, Max] | 37.5 [32.0, 43.0] | 33.0 [31.0, 38.0] | 45.0 [30.0, 57.0] | 31.0 [27.0, 35.0] | 32.0 [28.0, 32.0] | 34.0 [27.0, 63.0] | 40.0 [26.0, 49.0] | 27.0 [27.0, 27.0] | 26.5 [19.0, 30.0] | 34.0 [24.0, 54.0] | 32.0 [19.0, 57.0] | 34.0 [24.0, 63.0] |
| race | ||||||||||||
| Black or African-American | 1 (50.0%) | 0 (0%) | 1 (33.3%) | 0 (0%) | 1 (33.3%) | 1 (33.3%) | 2 (40.0%) | 1 (100%) | 0 (0%) | 4 (57.1%) | 5 (29.4%) | 6 (35.3%) |
| White | 1 (50.0%) | 3 (75.0%) | 1 (33.3%) | 2 (100%) | 2 (66.7%) | 1 (33.3%) | 1 (20.0%) | 0 (0%) | 4 (100%) | 3 (42.9%) | 9 (52.9%) | 9 (52.9%) |
| Asian | 0 (0%) | 1 (25.0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (5.9%) |
| American Indian or Alaska Native | 0 (0%) | 0 (0%) | 1 (33.3%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (5.9%) | 0 (0%) |
| Hispanic/Latinx | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (33.3%) | 2 (40.0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (11.8%) | 1 (5.9%) |
| gender | ||||||||||||
| Woman | 2 (100%) | 4 (100%) | 2 (66.7%) | 0 (0%) | 1 (33.3%) | 1 (33.3%) | 2 (40.0%) | 0 (0%) | 2 (50.0%) | 5 (71.4%) | 9 (52.9%) | 10 (58.8%) |
| Man | 0 (0%) | 0 (0%) | 1 (33.3%) | 2 (100%) | 2 (66.7%) | 2 (66.7%) | 3 (60.0%) | 1 (100%) | 2 (50.0%) | 2 (28.6%) | 8 (47.1%) | 7 (41.2%) |
| matrix_acc | ||||||||||||
| Mean (SD) | 0.313 (0.265) | 0.813 (0.161) | 0.917 (0.144) | 0.938 (0.0884) | 0.750 (0.217) | 0.917 (0.144) | 0.800 (0.112) | 0.750 (NA) | 0.781 (0.213) | 0.982 (0.0472) | 0.750 (0.234) | 0.912 (0.123) |
| Median [Min, Max] | 0.313 [0.125, 0.500] | 0.813 [0.625, 1.00] | 1.00 [0.750, 1.00] | 0.938 [0.875, 1.00] | 0.625 [0.625, 1.00] | 1.00 [0.750, 1.00] | 0.875 [0.625, 0.875] | 0.750 [0.750, 0.750] | 0.813 [0.500, 1.00] | 1.00 [0.875, 1.00] | 0.750 [0.125, 1.00] | 1.00 [0.625, 1.00] |
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: corrresp
Chisq Df Pr(>Chisq)
opinion_round 252.5145 1 <2e-16 ***
Deviant_threshold 6.0055 4 0.1987
matrix_cond 0.0297 1 0.8631
opinion_round:Deviant_threshold 2.9997 4 0.5579
opinion_round:matrix_cond 0.1250 1 0.7236
Deviant_threshold:matrix_cond 2.8825 4 0.5777
opinion_round:Deviant_threshold:matrix_cond 3.1339 4 0.5357
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
1 opinion_round.trend SE df asymp.LCL asymp.UCL z.ratio p.value
overall 0.167 0.0105 Inf 0.146 0.188 15.852 <.0001
Results are averaged over the levels of: Deviant_threshold, matrix_cond
Confidence level used: 0.95
$emmeans
Deviant_threshold emmean SE df asymp.LCL asymp.UCL z.ratio p.value
0 1.40 0.0941 Inf 1.22 1.59 14.903 <.0001
0.25 1.25 0.0868 Inf 1.08 1.42 14.404 <.0001
0.5 1.18 0.0884 Inf 1.01 1.36 13.382 <.0001
0.75 1.20 0.0889 Inf 1.03 1.38 13.551 <.0001
1 1.13 0.0949 Inf 0.94 1.31 11.865 <.0001
Results are averaged over the levels of: matrix_cond
Results are given on the logit (not the response) scale.
Confidence level used: 0.95
$contrasts
contrast estimate SE df asymp.LCL
Deviant_threshold0 - Deviant_threshold0.25 0.1527 0.128 Inf -0.1958
Deviant_threshold0 - Deviant_threshold0.5 0.2199 0.129 Inf -0.1317
Deviant_threshold0 - Deviant_threshold0.75 0.1983 0.129 Inf -0.1541
Deviant_threshold0 - Deviant_threshold1 0.2763 0.133 Inf -0.0877
Deviant_threshold0.25 - Deviant_threshold0.5 0.0672 0.124 Inf -0.2702
Deviant_threshold0.25 - Deviant_threshold0.75 0.0456 0.124 Inf -0.2927
Deviant_threshold0.25 - Deviant_threshold1 0.1236 0.128 Inf -0.2268
Deviant_threshold0.5 - Deviant_threshold0.75 -0.0216 0.125 Inf -0.3630
Deviant_threshold0.5 - Deviant_threshold1 0.0564 0.130 Inf -0.2970
Deviant_threshold0.75 - Deviant_threshold1 0.0780 0.130 Inf -0.2762
asymp.UCL z.ratio p.value
0.501 1.195 0.7542
0.571 1.706 0.4301
0.551 1.535 0.5397
0.640 2.070 0.2330
0.405 0.543 0.9828
0.384 0.367 0.9961
0.474 0.962 0.8720
0.320 -0.173 0.9998
0.410 0.435 0.9925
0.432 0.601 0.9750
Results are averaged over the levels of: matrix_cond
Results are given on the log odds ratio (not the response) scale.
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates
$emmeans
matrix_cond emmean SE df asymp.LCL asymp.UCL z.ratio p.value
high 1.23 0.0567 Inf 1.12 1.35 21.779 <.0001
low 1.23 0.0582 Inf 1.12 1.35 21.152 <.0001
Results are averaged over the levels of: Deviant_threshold
Results are given on the logit (not the response) scale.
Confidence level used: 0.95
$contrasts
contrast estimate SE df asymp.LCL asymp.UCL z.ratio p.value
high - low 0.00265 0.081 Inf -0.156 0.161 0.033 0.9739
Results are averaged over the levels of: Deviant_threshold
Results are given on the log odds ratio (not the response) scale.
Confidence level used: 0.95
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value
targetpair 393 393 1 464 1.5225
Deviant_threshold 67388 67388 1 464 260.8456
matrix_cond 228 228 1 464 0.8820
targetpair:Deviant_threshold 49180 49180 1 464 190.3684
targetpair:matrix_cond 11 11 1 464 0.0433
Deviant_threshold:matrix_cond 0 0 1 464 0.0001
targetpair:Deviant_threshold:matrix_cond 17 17 1 464 0.0651
Pr(>F)
targetpair 0.2179
Deviant_threshold <2e-16 ***
matrix_cond 0.3482
targetpair:Deviant_threshold <2e-16 ***
targetpair:matrix_cond 0.8353
Deviant_threshold:matrix_cond 0.9906
targetpair:Deviant_threshold:matrix_cond 0.7988
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
$emtrends
targetpair Deviant_threshold.trend SE df lower.CL upper.CL t.ratio p.value
DN -54.48 2.83 464 -60.0 -48.92 -19.277 <.0001
NN -6.79 2.28 464 -11.3 -2.32 -2.984 0.0030
Results are averaged over the levels of: matrix_cond
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
DN - NN -47.7 3.46 464 -54.5 -40.9 -13.797 <.0001
Results are averaged over the levels of: matrix_cond
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95
# A tibble: 4 × 14
# Groups: matrix_cond [2]
matrix_cond id term estimate std.error statistic p.value conf.low
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 high below_.5 Deviant_th… -12.8 6.61 -1.93 0.0552 -25.9
2 high above_.5 Deviant_th… -2.87 8.03 -0.357 0.721 -18.7
3 low below_.5 Deviant_th… -15.3 6.81 -2.25 0.0257 -28.8
4 low above_.5 Deviant_th… 0.0338 6.75 0.00502 0.996 -13.3
# ℹ 6 more variables: conf.high <dbl>, r.squared <dbl>, adj.r.squared <dbl>,
# df <dbl>, df.residual <int>, nobs <int>
# A tibble: 4 × 14
# Groups: matrix_cond [2]
matrix_cond id term estimate std.error statistic p.value conf.low
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 high below_.5 Deviant_th… -10.6 11.1 -0.947 0.345 -32.6
2 high above_.5 Deviant_th… -2.31 10.5 -0.221 0.825 -23.0
3 low below_.5 Deviant_th… -12.4 11.1 -1.12 0.263 -34.3
4 low above_.5 Deviant_th… 5.24 9.70 0.540 0.590 -14.0
# ℹ 6 more variables: conf.high <dbl>, r.squared <dbl>, adj.r.squared <dbl>,
# df <dbl>, df.residual <int>, nobs <int>
Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 2400 600.08 0.9361 0.4427
matrix_cond 1 12 11.98 0.0187 0.8913
deviance:matrix_cond 4 1385 346.30 0.5402 0.7063
Residuals 454 291031 641.04
$emmeans
deviance emmean SE df lower.CL upper.CL t.ratio p.value
0 56.6 2.73 454 51.2 62.0 20.707 <.0001
0.25 55.1 2.54 454 50.1 60.1 21.694 <.0001
0.5 50.6 2.60 454 45.5 55.7 19.436 <.0001
0.75 52.8 2.60 454 47.7 57.9 20.316 <.0001
1 51.1 2.79 454 45.7 56.6 18.336 <.0001
Results are averaged over the levels of: matrix_cond
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio
deviance0 - deviance0.25 1.506 3.73 454 -8.71 11.73 0.403
deviance0 - deviance0.5 6.037 3.77 454 -4.30 16.37 1.600
deviance0 - deviance0.75 3.825 3.77 454 -6.50 14.15 1.014
deviance0 - deviance1 5.469 3.91 454 -5.23 16.17 1.400
deviance0.25 - deviance0.5 4.531 3.64 454 -5.43 14.49 1.246
deviance0.25 - deviance0.75 2.319 3.63 454 -7.63 12.27 0.638
deviance0.25 - deviance1 3.963 3.77 454 -6.37 14.29 1.051
deviance0.5 - deviance0.75 -2.212 3.68 454 -12.28 7.86 -0.602
deviance0.5 - deviance1 -0.568 3.81 454 -11.01 9.88 -0.149
deviance0.75 - deviance1 1.644 3.81 454 -8.80 12.08 0.431
p.value
0.9944
0.4984
0.8489
0.6277
0.7242
0.9687
0.8315
0.9748
0.9999
0.9928
Results are averaged over the levels of: matrix_cond
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates
| 0 (N=88) |
0.25 (N=100) |
0.5 (N=97) |
0.75 (N=96) |
1 (N=83) |
Overall (N=464) |
|
|---|---|---|---|---|---|---|
| pred_maj | ||||||
| Yes | 14 (15.9%) | 18 (18.0%) | 15 (15.5%) | 19 (19.8%) | 20 (24.1%) | 86 (18.5%) |
| No | 74 (84.1%) | 82 (82.0%) | 81 (83.5%) | 77 (80.2%) | 62 (74.7%) | 376 (81.0%) |
| Missing | 0 (0%) | 0 (0%) | 1 (1.0%) | 0 (0%) | 1 (1.2%) | 2 (0.4%) |
# A tibble: 4 × 14
# Groups: pred_maj [2]
pred_maj id term estimate std.error statistic p.value conf.low conf.high
<lgl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 FALSE below_… Devi… -11.8 8.17 -1.45 0.148 -27.9 4.25
2 FALSE above_… Devi… -1.35 7.66 -0.177 0.860 -16.4 13.7
3 TRUE below_… Devi… -13.6 20.3 -0.669 0.507 -54.4 27.3
4 TRUE above_… Devi… 24.1 17.1 1.41 0.164 -10.2 58.4
# ℹ 5 more variables: r.squared <dbl>, adj.r.squared <dbl>, df <dbl>,
# df.residual <int>, nobs <int>
Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 2227 556.6 0.9086 0.4587
pred_maj 1 12304 12303.6 20.0843 9.402e-06 ***
deviance:pred_maj 4 2379 594.8 0.9710 0.4231
Residuals 452 276895 612.6
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| 0 (N=88) |
0.25 (N=100) |
0.5 (N=97) |
0.75 (N=96) |
1 (N=83) |
Overall (N=464) |
|
|---|---|---|---|---|---|---|
| pns_med | ||||||
| High | 40 (45.5%) | 39 (39.0%) | 36 (37.1%) | 43 (44.8%) | 34 (41.0%) | 192 (41.4%) |
| Low | 47 (53.4%) | 60 (60.0%) | 61 (62.9%) | 53 (55.2%) | 49 (59.0%) | 270 (58.2%) |
| Missing | 1 (1.1%) | 1 (1.0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.4%) |
# A tibble: 4 × 14
# Groups: pns_med [2]
pns_med id term estimate std.error statistic p.value conf.low conf.high
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 High below_.5 Devi… -10.7 13.1 -0.818 0.415 -36.7 15.2
2 High above_.5 Devi… 1.43 11.9 0.121 0.904 -22.1 24.9
3 Low below_.5 Devi… -13.8 9.60 -1.44 0.152 -32.8 5.14
4 Low above_.5 Devi… 0.669 8.78 0.0761 0.939 -16.7 18.0
# ℹ 5 more variables: r.squared <dbl>, adj.r.squared <dbl>, df <dbl>,
# df.residual <int>, nobs <int>
Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 2465 616.17 0.9641 0.4269
pns_med 1 519 519.01 0.8121 0.3680
deviance:pns_med 4 82 20.57 0.0322 0.9980
Residuals 452 288883 639.12
| 0 (N=464) |
1 (N=464) |
2 (N=464) |
3 (N=464) |
4 (N=464) |
5 (N=464) |
6 (N=464) |
7 (N=464) |
Overall (N=3712) |
|
|---|---|---|---|---|---|---|---|---|---|
| trialnum | |||||||||
| 0 | 73 (15.7%) | 66 (14.2%) | 66 (14.2%) | 66 (14.2%) | 60 (12.9%) | 55 (11.9%) | 46 (9.9%) | 59 (12.7%) | 491 (13.2%) |
| 1 | 67 (14.4%) | 62 (13.4%) | 53 (11.4%) | 64 (13.8%) | 72 (15.5%) | 54 (11.6%) | 60 (12.9%) | 60 (12.9%) | 492 (13.3%) |
| 2 | 51 (11.0%) | 49 (10.6%) | 66 (14.2%) | 51 (11.0%) | 50 (10.8%) | 60 (12.9%) | 49 (10.6%) | 66 (14.2%) | 442 (11.9%) |
| 3 | 67 (14.4%) | 53 (11.4%) | 55 (11.9%) | 53 (11.4%) | 49 (10.6%) | 69 (14.9%) | 57 (12.3%) | 61 (13.1%) | 464 (12.5%) |
| 4 | 53 (11.4%) | 58 (12.5%) | 58 (12.5%) | 65 (14.0%) | 68 (14.7%) | 60 (12.9%) | 54 (11.6%) | 37 (8.0%) | 453 (12.2%) |
| 5 | 57 (12.3%) | 61 (13.1%) | 54 (11.6%) | 64 (13.8%) | 47 (10.1%) | 67 (14.4%) | 74 (15.9%) | 55 (11.9%) | 479 (12.9%) |
| 6 | 55 (11.9%) | 54 (11.6%) | 55 (11.9%) | 56 (12.1%) | 62 (13.4%) | 53 (11.4%) | 61 (13.1%) | 59 (12.7%) | 455 (12.3%) |
| 7 | 41 (8.8%) | 61 (13.1%) | 57 (12.3%) | 45 (9.7%) | 56 (12.1%) | 46 (9.9%) | 63 (13.6%) | 67 (14.4%) | 436 (11.7%) |